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will develop the specific training scenarios and guidance. Finally you will perform an experimental validation of the efficacy of the new training materials with educators, relevant student groups and
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to extend the operational lifespan and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way
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the operational lifespan and reduce the overall weight of wind turbines. By innovating ways to lower mechanical loads on critical components and optimizing material usage, we aim to pave the way for a truly
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in September 2026. Physical learning is an emerging paradigm in which materials adapt their behavior through local physical rules, without digital computation. Despite rapid experimental progress, it
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new functional materials, in partnership with academia and industry. The institute is located at Amsterdam Science Park and currently employs about 140 researchers and 80 support employees. www.amolf.nl
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, with a focus on crack initiation, propagation, and damage evolution. These structures are characterised by large wall thicknesses, irregular bond patterns, varying material quality, and exposure
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understanding, design, production including application and product improvement, materials, processes and (mechanical) systems. ME is a dynamic and innovative faculty with high-tech lab facilities and
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For practical questions regarding the application procedure: Maarit van Gammeren m.s.k.van.gammeren@hum.leidenuniv.nl Application procedure Applicants are invited to submit the following materials before 30 April
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and imaging capabilities, and on applying THz (emission) microscopy to study 2D materials and 2D heterostructures. The microscope will use femtosecond lasers to generate and detect terahertz pulses
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feed into this vision. The intended start date is July–August 2026. Job requirements PhD in machine learning, artificial intelligence, computational chemistry, computational materials science, or a